How Data Makes It Easier Than Ever to Become an Amazing Driver

Sometimes truth really is stranger than fiction. No Hollywood screenwriter would have the gall to pitch a movie with the kind of plot we saw unfold in real life this past weekend at Barcelona. Can you even imagine the lunch meeting where such a pitch would occur?

So, there's this sixteen-year-old kid. The youngest-ever driver in Formula One, right? And nobody thinks he should be allowed to drive, but it turns out he's actually pretty good. And then he gets promoted to one of the top teams when the driver for that team keeps crashing and doing crazy stuff. But this top team hasn't won in a long time. Nobody ever wins except for the two guys from the evil German team. But then they RUN INTO EACH OTHER, okay? And our hero, who has just turned eighteen, wins the race on strategy! And he holds off one of the most talented F1 drivers in history all the way to the end—and impresses that driver so much that at the end of the race there's this big congratulatory moment!

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The plot of Sylvester Stallone's much-derided Driven looks positively realistic next to Max Verstappen's dream debut for Red Bull. Yet all of the pieces for such a triumph have been in place for some time now, both in Formula One and elsewhere. The science of driver training has advanced by leaps and bounds in the simulator era, and it's easier than ever to use advanced data analysis to coach relatively inexperienced drivers through brilliant performances. More importantly, the tools used to make Max Verstappen the youngest winner in Formula One history are available, in a somewhat more modest form, to amateur racers all the way down to the ChumpCar and LeMons level.

Just fifty short years ago, most race drivers thought speed couldn't be taught. You either had "it" or you didn't. There wasn't much consensus on what "The Line" should be. Very few racers understood how to properly trail-brake. The very idea of taking classes on how to race offended a lot of drivers. Teaching grown men how to get around a racetrack? You might as well go to their bedrooms and try to teach them what to do with their wives!

You might as well go to their bedrooms and try to teach them what to do with their wives!

Carroll Shelby, Bob Bondurant, Bertil Roos, and others attacked that ignorance head-on, developing a standardized racing curriculum and then proving that it was possible to make heroes out of zeroes through rigorous training and feedback. The quality of amateur and professional racers increased dramatically through the Eighties and Nineties. But there was still one missing piece in the driver-training puzzle.

That piece was, quite simply, data. Once it became possible to measure every aspect of a driver's performance, from corner speed at apex to brake pressure at the end of a long straight, the "secrets" that separated great drivers from merely good ones became immediately transparent. By 2005, virtually every professional racing team in the world was using detailed data to erase gaps between teammates and improve laptimes. Thanks to companies like Traqmate and Autosport Labs, those same tools are now available to amateur drivers as well. A detailed data-analysis session will produce measurable results for pretty much every racer with the intelligence and patience to see it through.

I witnessed the efficiency of this process first-hand during a very short stint in the Grand-Am Koni Challenge back in 2009. The team that I was on performed detailed data work between sessions, comparing performance across six drivers to create theoretical best laps then coaching each one of the drivers towards that lap. The result? A season championship for a relatively inexperienced driver and some very nice trophies for almost everybody involved.

The data available to European formula car teams is much more sophisticated than what we had in Grand-Am. As a consequence, there's no longer any guessing about why one driver is faster than another. It's all in the data. Does Driver A brake one tenth of a second later than Driver B but apply ten pounds more pressure to the brake pedal upon initial application? Everybody on the team will know it, and everybody on the team will be able to determine what's necessary to get all the drivers on the fastest possible strategy. All you need is a driver team that is coachable and willing to do whatever they're told.

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That doesn't mean that any young driver could do what Max Verstappen did. Not only is Max a superb talent in all areas of driving, he also possesses nerves of steel, as was readily apparent to anybody who watched him hold off Raikkonen for half the race. No amount of poring over data will save the day when you have a World Champion in a faster car behind you. That's all down to heart and courage and plain old-fashioned balls. But having a data-driven training methodology means that young drivers don't have to waste years watching and learning on the racetrack. They can be immediately coached to the fastest possible laptimes.

Having a data-driven training methodology means that young drivers don't have to waste years watching and learning on the racetrack.

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The one thing you can't learn from data is racecraft, but most young F1 prospects arrive at the sport with over a decade's worth of hard-fought karting wins under their belts. They already know how to make every pass in the book and they have plenty of experience doing it. Lewis Hamilton proved that when he arrived in Formula One as a rookie and immediately took the fight to Fernando Alonso in the most uncompromising manner possible.

I feel confident in saying that every trackday driver and racer above the novice group can benefit from a data-driven approach to going faster. This doesn't mean putting your phone with "Harry's Lap Timer" in a suction-cup rig on your dashboard; that's just a great way to crash while chasing a lap time that might or might not be possible for you and your car on that particular day. I'm talking about recording a complete suite of data and then looking at it between sessions to see where you're inconsistent, where you are fast, and where you're just plain slow. Using that data to set achievable goals in every session is a great way to get fast in a big hurry. It will also improve your understanding of everything from vehicle dynamics to tire management.

It's already too late for most of us to be the next Max Verstappen. But that doesn't mean that we can't use the right tools to improve our driving and increase our enjoyment of open-track driving or amateur racing. In the end, what makes Max's win so satisfying is the same thing that keeps so many of us coming back to the racetrack weekend after weekend: the attempt to combine flawless technical proficiency with the human elements of courage and joy. When you do everything right, even for just one lap or just one part of a lap, you're getting a small taste of how Max must have felt when he saw the checkered flag waving at the end of last weekend's race. It's nice to watch other people win, but it's even nicer to be the hero of your own movie, no matter how improbable the plot.

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Born in Brooklyn but banished to Ohio, Jack Baruth has won races on four different kinds of bicycles and in seven different kinds of cars. Everything he writes should probably come with a trigger warning. His column, Avoidable Contact, runs twice a week.

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